TY - JOUR N2 - This paper presents mechanical fault detection in squirrel cage induction motors (SCIMs) by means of two recent techniques. More precisely, we have analyzed the rolling element bearing (REB) faults in SCIM. Rolling element bearing faults constitute a major problem among different faults which cause catastrophic damage to rotating machinery. Thus early detection of REB faults in SCIMs is of crucial importance. Vibration analysis is among the key concepts for mechanical vibrations of rotating electrical machines. Today, there is massive competition between researchers in the diagnosis field. They all have as their aim to replace the vibration analysis technique. Among them, stator current analysis has become one of the most important subjects in the fault detection field. Motor current signature analysis (MCSA) has become popular for detection and localization of numerous faults. It is generally based on fast Fourier transform (FFT) of the stator current signal. We have detailed the analysis by means of MCSA-FFT, which is based on the stator current spectrum. Another goal in this work is the use of the discrete wavelet transform (DWT) technique in order to detect REB faults. In addition, a new indicator based on the MCSA-DWT technique has been developed in this study. This new indicator has the advantage of expressing itself in the quantity and quality form. The acquisition data are presented and a comparative study is carried out between these recent techniques in order to ensure a final decision. The proposed subject is examined experimentally using a 3 kW squirrel cage induction motor test bed. L1 - http://journals.pan.pl/Content/113169/PDF/14_571-582_01009_Bpast.No.67-3_06.02.20.pdf L2 - http://journals.pan.pl/Content/113169 PY - 2019 IS - No. 3 EP - 582 DO - 10.24425/bpasts.2019.129655 KW - motor current signature analysis (MCSA) KW - discrete wavelet transform (DWT) KW - rolling element bearing faults KW - rotor eccentricity KW - stator current spectrum A1 - Bessous, N. A1 - Sbaa, S. A1 - Megherbi, A.C. VL - 67 DA - 30.06.2019 T1 - Mechanical fault detection in rotating electrical machines using MCSA-FFT and MCSA-DWT techniques SP - 571 UR - http://journals.pan.pl/dlibra/publication/edition/113169 T2 - Bulletin of the Polish Academy of Sciences Technical Sciences ER -